Hunan University of Science and Technology - China
Author Profiles
Scopus
Orcid
Early Academic Pursuits
Assist. Prof. Dr. Xiangnan Liu, born in Shaoyang, Hunan, began his academic journey with an early interest in Mechanical Engineering and measurement technologies. His dedication to scientific research led him to pursue a PhD in Mechanical Engineering at the South China University of Technology. During this time, he developed a strong foundation in fatigue analysis, vibration response, and durability testing, laying the groundwork for his future academic and research contributions. His outstanding doctoral work established him as a promising scholar in the field of Mechanical Engineering.
Professional Endeavors
Dr. Liu has cultivated a distinguished career in both academia and industry. He is currently an Associate Professor at the School of Mechanical and Electrical Engineering, Hunan University of Science and Technology (2025–present), where he also serves as Deputy Director of the Department of Mechanical Electronics and Measurement and Control Instruments. Alongside his university role, he is a Postdoctoral Fellow at Xuelong Group Co., Ltd. since July 2025. His professional endeavors extend to significant administrative and collaborative roles, such as serving as a correspondence review expert for the National Natural Science Foundation of China, a senior member of the Chinese Society of Mechanical Engineers, and Director of the Hunan Instrument Society. His dual commitment to academia and applied research underscores his dedication to advancing Mechanical Engineeringin China and internationally.
Contributions and Research Focus
Dr. Liu’s research focuses on fatigue strength, life prediction, and durability testing of rubber vibration damping products. His contributions include pioneering work in vibration response and strength analysis of rubber materials, fatigue testing of automotive parts, and innovative methods for cooling fan blade fatigue analysis. He leads major projects such as the National Natural Science Foundation Youth Project on fatigue damage evolution mechanisms, as well as multiple school-enterprise collaborations focusing on automotive rubber components, air spring hysteresis performance, and fatigue life of metal pipes. His research is not only theoretical but also highly practical, bridging the gap between Mechanical Engineering theory and industrial application.
Impact and Influence
The impact of Dr. Liu’s work is reflected in his leadership roles, his contributions to national-level projects, and his extensive publications in high-impact journals, including the International Journal of Fatigue, Fatigue & Fracture of Engineering Materials & Structures, Measurement, and the Chinese Journal of Mechanical Engineering. His studies have advanced understanding of multi-axial fatigue, probabilistic fatigue life prediction, and artificial intelligence applications in structural fatigue. He has also played an influential role in education reform by integrating ideological and political elements into engineering curricula. His influence extends through mentorship, as he has guided students to publish in leading journals and win prestigious competitions.
Academic Cites
Dr. Liu’s body of work, consisting of more than 20 high-quality papers, is widely cited in the field of Mechanical Engineering, underscoring the scholarly value of his research. His contributions to probabilistic fatigue models, neural network-based life prediction, and load spectrum editing are frequently referenced by academics and professionals alike. His recognition as part of the 2024 Wiley China Excellent Author Program further highlights the significance and global reach of his academic work.
Legacy and Future Contributions
Looking ahead, Dr. Liu is poised to further solidify his legacy in Mechanical Engineering His ongoing projects in fatigue strength and life prediction are expected to result in innovative technologies and predictive models that will benefit both academia and industry. His leadership in research, combined with his commitment to education and mentorship, ensures that his influence will extend to future generations of engineers. By bridging academic theory with industrial applications, Dr. Liu’s future contributions promise to strengthen the durability and reliability of mechanical systems in automotive, aerospace, and energy sectors.
📝Mechanical Engineering
Assist. Prof. Dr. Xiangnan Liu has established himself as a leading scholar in Mechanical Engineering, with impactful research on fatigue strength, vibration damping, and durability testing. His numerous publications, projects, and academic achievements have advanced the global field of Mechanical Engineering, while his mentorship and educational reforms contribute to shaping the discipline’s future. His legacy in Mechanical Engineering continues to grow through innovative research, applied industrial collaborations, and academic leadership.
Notable Publication
Physics‐Informed Neural Network Model for Predicting the Fatigue Life of Natural Rubber Under Ambient Temperature Effects
Authors: Yujia Liu; Wen‐Bin Shangguan; Xiangnan Liu; Xuepeng Qian
Journal: Fatigue & Fracture of Engineering Materials & Structures
Year: 2025
Accelerated fatigue bench test method for rubber vibration isolators based on load spectrum compilation
Authors: Xiangnan Liu; Xuepeng Qian; Yi Xi
Journal: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Year: 2025
Comparison and experiment validation of fatigue data editing methods for vehicle component
Authors: Jingwei Xu; Xiangnan Liu
Journal: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Year: 2025
Improving Fatigue Life Prediction of Natural Rubber Using a Physics‐Informed Neural Network Model
Authors: Yingshuai Sun; Xiangnan Liu; Qing Yang; Xuelai Liu; Kuanfang He
Journal: Fatigue & Fracture of Engineering Materials & Structures
Year: 2025
Multi-axis fatigue load spectrum editing for automotive components using generalized S-transform
Authors: Xiangnan Liu; Jinghai Tan; Shangbin Long
Journal: International Journal of Fatigue
Year: 2024
A unified probabilistic fatigue life prediction model for natural rubber components considering strain ratio effect
Authors: Xiangnan Liu; Xuezhi Zhao; Xiao‐Ang Liu
Journal: Fatigue & Fracture of Engineering Materials & Structures
Year: 2023
Natural rubber components fatigue life estimation through an extreme learning machine
Authors: Xiangnan Liu; Xiao-Li Wang
Journal: Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications
Year: 2023